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Millions of people suffer from various diseases of the central nervous system such as stroke, Parkinson’s disease, Alzheimer’s disease, and hydrocephalus. To improve the treatment options available, a better understanding of the intracranial dynamics is required. The understanding of intracranial dynamics leads to quantification of fluid flow, cerebrospinal blood pressure, and extension of brain vasculature during the cardiac cycle. One such quantification method, used to simulate the physiological conditions in the brain, is the computer program MATLAB, and one proposed approach is using a “compartmental” model, where arteries, veins, choroids plexus, and other areas and vessels in the brain are lumped as compartments to simulate the intracranial dynamics under normal and hydrocephalic conditions. A dynamic model, built on previous work with additional compartments, compiled in MATLAB, was used to compare the validity of the previous models. In addition, a network model was generated using the principles of the compartmental model. The model was used to accurately predict normal pathological conditions of blood flow through the brain. The results generated using the model generator and the MATLAB program were very similar to the normal physiological values stated in literature. Thus, the mathematical model is consistent and can be used to simulate other pathological conditions of the brain such as hydrocephalus to gain a better understanding of what occurs in such diseases, allowing us to properly treat such pathological conditions.

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